Sensitivity-Based Adaptive Learning Rules for Binary Feedforward Neural Networks

This paper proposes a set of adaptive learning rules for binary feedforward neural networks (BFNNs) by means of the sensitivity measure that is established to investigate the effect of a BFNN's weight variation on its output. The rules are based on three basic adaptive learning principles: the...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2012-03, Vol.23 (3), p.480-491
Hauptverfasser:	Zhong, Shuiming, Zeng, Xiaoqin, Wu, Shengli, Han, Lixin
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Adaptive learning algorithm Algorithms Applied sciences Artificial Intelligence binary feedforward neural networks Biological neural networks Computer science control theory systems Connectionism. Neural networks Control systems Control theory Databases, Factual - statistics & numerical data Disturbances Exact sciences and technology Feedforward Feedforward neural networks Learning learning rule Learning systems Neural networks Neural Networks (Computer) Neurons Sensitivity Studies Training Weight measurement
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!